Thank you for writing this. Dana

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You state "Industry does not fund studies to answer questions about nature. Industry funds (and designs) studies to show that their product works. This is not nefarious."

I posit that this practice is indeed, profoundly nefarious and is destructive to society.

At it's core, the pharmaceutical industry is at war with nature, damaging and altering the immune system w/most products while combating any attempts by other entities to support the inmune system and treat chronic disease at it's root cause (well illustrated the last three years via mRNA products and denial of superiority of natural immunity)

I could go on and say that this war against nature effects far more than just extensive massive medical harm (autoimmunity, cancer, heart disease) but also has a detrimental effect on career, family structure, crime, education, military readiness and more.

The body in its' natural form, should be supported, not injected and ingested with foreign substances.

BUT because you cannot patent mother nature, the pharma industry tries to modify, mimic or stop the immune system by any synthetic, patented & profitable means possible because that's all they know. NOT because that's all that works. Look at health outcomes. It doesn't work.

I'm sorry...i just couldn't get past the "it's not nefarious".

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Thank you, Dr. Mandrola, for giving us a good example of overgeneralizing the results of a study to support an unwarranted conclusion. Your explanation is easy for a layperson to understand. Much appreciated!

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On this topic of bias in a study, I am curious on your thoughts on the authors of the recent study "Lifting Universal Masking in Schools — Covid-19 Incidence among Students and Staff" (NEJM) not mentioning their bias in the declarations.

While Vinay Prasad already pointed out the failure to account for testing differences in the two groups, I was giving this another look after Katelyn Jetelina promoted it as proof masks work in school last week and realized the authors had successfully organized a change.org petition [1] during the study period to return masks to schools in Boston and didn't note this in disclosures. Another author of the study also penned the op ed "It's too soon to lift the school mask mandate" in the Boston Globe [2], also not disclosed.

I'm curious if these are things which you would expect to be disclosed, or, if they get a pass because the conflicts don't involve financial benefits? This bias might explain how they can find in observational studies what RCTs cannot detect (that loose cloth masks have 30% reduction power in cases), or, might explain why the authors didn't appear to realize 13 of the schools they counted in the "Mask" pool actually received exemptions from the policy [3].



[1] https://twitter.com/EpiEllie/status/1429102872470433795




[3] You can cross reference this list with table S1 of the study to see the 13 schools they missed:


Example of one of the schools lifting it: https://www.kingphilip.org/important-mask-update-2/

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How is it that a lay person (engineering but nothing to do with medicine) can spot the issue a mile away and yet gets published w/o backlash? As I read the 5 bullet points, the stacking of the cards was apparent. How can this be? Oh. Right. Funding source. SMH

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Thank you for the clear and very concise explanation!

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Well done. This exactly correct, the desired result of any trial can be baked into the subtle aspects of methodology, influenced by the sponsor, of course.

The indictment here, however, is on our superficial "tweet" culture and our gullibility... That top line results encapsulated in a tweet (or ad, sales pitch,or whatever) will mostly never receive intellectual scrutiny, and will still influence perception.

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Twitter reminds me of the guy on the street corner with an overcoat on, selling “genuine Rolexes” as he opens one side of the coat exposing rows of them. Sometimes I think scientists, etc., are so used to the world they live in that they can’t see that they are either catering to that guy on the corner or have a fistful of watches that they themselves are selling. And I’ll be the first one to say I’ve fallen for a few scams over the years.

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Fascinating! And so frustrating.

There’s also bias that runs so deep nobody in the study even knows it’s there, like a fish doesn’t know it’s wet. More here:


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Awesome breakdown, thanks. Important concept to comprehend in an era when everyone including those not in the field loves sharing any inkling of data that confirms their biases

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